Abstract: A method and authentication system for alleviating authenticity of sensors in biometric authentication is disclosed. The authentication system receives fingerprint data from a plurality of sensing devices configured in the authentication system and extract one or more attributes associated with the fingerprint data. An expanded value for each of the one or more attributes is determined based on one or more predefined techniques. The authentication system (101) trains a model associated with authentication of fingerprints using the one or more attributes and corresponding expanded value. Further, one or more errors associated with the fingerprint data are predicted based on fingerprint data received over a period of time in real-time and the model is retrained based on the predicted one or more errors to alleviate authenticity of sensors in biometric authentication.

Abstract: A method and device for database design and creation is disclosed. The method includes determining ranks for each of a plurality of variables in each of a plurality of databases based on at least one attribute associated with each of the plurality of variables. The method further includes arranging each of the plurality of variables in a sequence with respect to an associated database from the plurality of databases. The method includes computing a correlation coefficient between the plurality of variables across the plurality of databases based on the sequence of arrangement. The method further includes determining based on the correlation coefficient, whether a relationship exists between one or more of the plurality of variables across the plurality of databases. The method includes creating a database using the plurality of databases based on the relationship, when the relationship exists between the one or more of the plurality of variables.

Abstract: This disclosure relates generally to machine design, and more particularly to method and system for generating physical design parameters of an object. In one embodiment, the method includes receiving a graphical design of the object along with a desired axis of rotation, categorizing the object into an object type based on the graphical design of the object and the desired axis of rotation of the object, and determining a regression weight and a regression estimate for each of the plurality of physical design parameters based on the object type, determining a plurality of proximity metrics based on the regression estimate for each of the plurality of physical design parameters, adjusting the regression weight for each of the plurality of physical design parameters based on the plurality of proximity metrics, and generating a value for each of the plurality of physical design parameters based on the corresponding adjusted regression weight.

Abstract: A method and system for executing processes in an operating system is disclosed. The method may include assigning a tag Identifier (ID) and a first tree ID to each of a plurality of processes based on associated at least one attribute. The method may further include determining content patterns associated with each of the plurality of processes using a deep learning network. The method may include assigning a second tree ID to each of at least one process from the plurality of processes based on the identified content pattern. The method may further include generating a set of clusters for the plurality of processes based on the second tree ID assigned to each of the at least one process. The method may include executing each process within a cluster from the set of clusters based on execution of a single process within the cluster.

Abstract: The present invention discloses a method and a system for managing cache memory. The system comprising a processor is configured to receive datasets from one or more applications, segregate the received datasets into one or more data blocks, identify a checkpoint from previously created checkpoints stored in a virtual cache corresponding to the one or more data blocks, wherein the checkpoints are previously created based on frequency of repetition of each of the one or more data blocks and association between the each of the one or more data blocks, recall a sequence of previously stored data blocks from main memory based on the identified checkpoint, and send the sequence of previously stored data blocks to the one or more applications for execution, thereby managing cache memory.

Abstract: Disclosed herein is a method and Serially Attached SCSI (SAS) controller for transmitting data using SCSI. In an embodiment, a plurality of I/O operations received from a storage unit are fragmented into a plurality of blocks. Further, each of the plurality of blocks are mapped with corresponding memory drives. Thereafter, a reduced number of virtual lanes required for transmitting the plurality of blocks to the corresponding memory drives is estimated. Finally, the reduced number of virtual lanes are created for transmitting the plurality of blocks to the corresponding memory drives. In an embodiment, the present disclosure uses virtual lanes for transmitting data, thereby eliminating requirement of dedicated, physical lanes for transmitting the data. Consequently, according to embodiments of present disclosure, the SAS controller may be configured to simultaneously activate multiple virtual lanes for completing the data transmission, thereby resulting in faster and reliable data transmission.

Abstract: The present disclosure relates to method and system for operating storage drives to increase lifecycle of the storage drives. A drive manager receives a plurality of parameters of a plurality of storage drives and determines operational state of one or more storage drives from the plurality of storage drives as unhealthy. Further, the drive manager identifies an application frequently retrieving data from the one or more storage drives and further determines one or more memory locations in the one or more storage drive from where the data is retrieved frequently. Thereafter, the data present in the one or more memory locations are stored in a temporary storage and is provided to the application during a future data retrieval cycle. Thus, the application may not retrieve data from the one or more storage drives. Hence, the lifecycle of the one or more storage drives can be increased.

Abstract: A method and system of transmitting packets within a network is disclosed. The method includes determining frequency and sequence of transmission for a plurality of packets within the network. The method further includes identifying a set of recurrent packets from the plurality of packets based on the determined frequency and sequence of transmission. The method includes training a neural network based on the identified set of recurrent packets to identify recurrent packets. The method further includes generating a packet checkpoint based on the trained neural network. The method includes regenerating one or more of the set of recurrent packets in response to a request for the set of recurrent packets, based on the packet checkpoint.

Abstract: The present disclosure discloses method and policy management system for managing policies in network security system. The policy management system receives one or more data packets from a request source of plurality of request sources, monitors at least one of, an inbound transmission time, an out bound transmission time and a jitter hit rate associated with the one or more data packets and a hit count, a current hit count, last hit time and hit per policy associated with each of plurality of policies of network firewall in real-time. Based on monitoring, policy management system estimates a hit count percentage for each of the plurality of policies and groups plurality of policies into plurality of policy clusters based on hit count percentage associated with each of the plurality of policies. Thus, the present disclosure provides an efficient way of managing network firewall policies without any human intervention.

Abstract: This disclosure relates to method and system for data compression and data storage optimization. The method of compression may include converting each data block into a matrix, compressing each data block by processing the corresponding matrix to form a minimum state matrix based on a sequential set of compression rules, deriving a granular metadata for each data block based on the corresponding minimum state matrix, and storing the granular metadata and the sequential set of compression rules for each data block. Further, the method of decompression may include accessing a granular metadata and a sequential set of compression rules for each data block, deriving a minimum state matrix for each data block based on the corresponding granular metadata, decompressing each data block by processing the corresponding minimum state matrix to form a matrix based on the sequential set of compression rules, and building each data block from the corresponding matrix.

Abstract: The present disclosure relates to method and system for operating storage drives to increase lifecycle of the storage drives. A drive manager receives a plurality of parameters of a plurality of storage drives and determines operational state of one or more storage drives from the plurality of storage drives as unhealthy. Further, the drive manager identifies an application frequently retrieving data from the one or more storage drives and further determines one or more memory locations in the one or more storage drive from where the data is retrieved frequently. Thereafter, the data present in the one or more memory locations are stored in a temporary storage and is provided to the application during a future data retrieval cycle. Thus, the application may not retrieve data from the one or more storage drives. Hence, the lifecycle of the one or more storage drives can be increased.

Abstract: This disclosure relates to method and system for annotating tokens for natural language processing (NLP). In one embodiment, the method may include segmenting a plurality of corpus based on each of a plurality of instances, deriving a plurality of entities for each of the plurality of instances based on at least one of a machine learning technique or a deep learning technique, determining a word vector for each of the plurality of entities associated with each of the plurality of instances, and labelling a plurality of tokens for each of the plurality of instances. It should be noted that the plurality of tokens associated with the plurality of entities may be identified based on a frequency of each of the plurality of entities.

Abstract: The present disclosure discloses a method and a system for storing data in a data storage system of a Virtual Storage Area Network (VSAN). The method comprises receiving, by a server management system, a request message for storing data, from an array controller of a first node among a plurality of nodes of a Virtual Storage Area Network (VSAN) cluster, where each of the plurality of nodes comprises a pair of array controllers and a data storage unit, identifying a second node from the plurality of nodes, for storing the data in a data storage unit of the second node and routing the data to an array controller of the second node, for storing the data in the data storage unit, for effectively utilizing the data storage unit of the VSAN network.

Abstract: This disclosure relates to method and system for optimizing memory requirement for training an artificial neural network (ANN) model employed for natural language processing (NLP). In one embodiment, the method may include receiving a plurality of training parameters and a plurality of model parameters, selecting a set of model parameters from among the plurality of model parameters for training the ANN model based on a characteristic and an architecture of the ANN model, masking the set of model parameters in one or more layers of the ANN model based on a set of pre-defined rules to generate a set of masked model parameters, determining an amount of memory required for training the ANN model based on the set of masked model parameters, and providing the set of masked model parameters for training the ANN model when the amount of memory required is less than a determined threshold.

Abstract: A method and system of transmitting packets within a network is disclosed. The method includes determining frequency and sequence of transmission for a plurality of packets within the network. The method further includes identifying a set of recurrent packets from the plurality of packets based on the determined frequency and sequence of transmission. The method includes training a neural network based on the identified set of recurrent packets to identify recurrent packets. The method further includes generating a packet checkpoint based on the trained neural network. The method includes regenerating one or more of the set of recurrent packets in response to a request for the set of recurrent packets, based on the packet checkpoint.

Abstract: A method and device for determining operation of an autonomous device is disclosed. The method includes receiving pixel data and sound data associated with an environment at an instance of time, wherein the pixel data is received from least an image sensor associated with the autonomous device, and wherein the sound data is received from at least four sound sensors placed in a quadrilateral configuration on the autonomous device. Each quadrant of the pixel data is associated with each of the at least four sound sensors. The sound data received is mapped the to the matrix to identify one or more pixels in the matrix corresponding to the sound data based on a difference in amplitude between a first sound sensor of the at least four sound sensors recording maximum sound amplitude with a plurality of second sound sensors of the at least four sound sensors.

Abstract: A method of managing resources in a cloud environment is disclosed. The method includes receiving a plurality of parameters associated with an event. The method further includes comparing a value of each of the plurality of parameters with a predefined threshold range. The method includes converting the value of each of the plurality of parameters into a vector, when the value of each of the plurality of parameters is within the predefined threshold range. The method further includes training a neural network based on the vector of the value of each of the plurality of parameters, wherein the neural network is trained to manage the event. The method includes storing an output of the trained neural network in a database in response to the training. The output corresponds to management of the event and the database further comprises a mapping of the event to the trained neural network.

Abstract: A method of managing Input Output per Second (IOPS) in Fiber Channel network topology is disclosed. The method includes initializing a plurality of network parameters into dependent variables and independent variables. The method includes performing multilinear regression analysis on at least one of the dependent variables and the independent variables to predict a value of at least one dependent variable. The method includes clustering each of a plurality of switches into a plurality of categories based on the predicted value. The method includes determining a plurality of routes between source and destination switches associated with an lops request. The method includes establishing a connection between the source and destination switches through a shortest route including a subset of switches. The method includes modulating, for each switch in the subset, a bandwidth according to an IOPS associated with the IOPS request and a category associated with each switch in the subset.

Abstract: A method of managing Input Output per Second (IOPS) in Fiber Channel network topology is disclosed. The method includes initializing a plurality of network parameters into dependent variables and independent variables. The method includes performing multilinear regression analysis on at least one of the dependent variables and the independent variables to predict a value of at least one dependent variable. The method includes clustering each of a plurality of switches into a plurality of categories based on the predicted value. The method includes determining a plurality of routes between source and destination switches associated with an IOPS request. The method includes establishing a connection between the source and destination switches through a shortest route including a subset of switches. The method includes modulating, for each switch in the subset, a bandwidth according to an IOPS associated with the IOPS request and a category associated with each switch in the subset.

Abstract: Embodiments of the present disclosure disclose a system and a method for resolving error in an open stack operating system (OS). An error code relating to an error in an open stack OS associated with the error resolution system may be retrieved. One or more services associated with the error code may be determined and at least one of one or more log files from the open stack OS and a resolver may be retrieved. The one or more services are enabled in the error resolution system for the retrieving. Further, a predefined action plan based on the one or more log files and the resolver may be determined. The error in the open stack OS is resolved based on the determined predefined action plan.